We aim to explore approaches based on neural networks and beyond, examining alternative AI methodologies that challenge and expand our current understanding of intelligence.
The event will foster interdisciplinary discussions on innovative methods and ideas, including Physics-Inspired Machine Learning, new statistical approaches, Quantum Machine Learning, Bayesian Methods, Neurosymbolic Methods, Symbolic AI, Automated Theorem Proving, Probabilistic Programming Languages, Variational Methods, Algebraic Machine Learning, Category Theory applied to AI and Compressive Sensing.